• COVID-19
• 02 engineering and technology close

Cette contribution s’intéresse à l’impact de la pandémie de COVID-19 sur les Établissements et Services d’Aide par le Travail (ESAT) français à partir d’entretiens conduits auprès de directeurs d’établissements situés dans le milieu rural et urbain de la Région Auvergne-Rhône-Alpes (France). Afin de situer les ESAT dans leur contexte national, un premier temps est consacré à rappeler la genèse et le fonctionnement de ce dispositif, mis en place pour favoriser l’insertion sociale et professionnelle des travailleurs en situation de handicap, dont l’originalité réside dans l’articulation d’une logique médico-sociale à une logique économique. Nous cherchons ensuite à montrer comment les ESAT se sont organisés pour assurer l’accompagnement médico-social de leurs travailleurs malgré l’obligation de distanciation. Puis, analysé au prisme de l’ancrage territorial et de la notion de proximité qui lui est associée, nous nous intéressons à l’impact du confinement sur l’équilibre économique de ces établissements pour montrer que la crise sanitaire a moins affecté les établissements à vocation majoritairement agricole implantés en milieu rural que ceux, plus orientés vers la sous-traitance industrielle, localisés en milieu urbain. This contribution focuses on the impact of the COVID-19 pandemic on French support and work assistance establishment (ESAT) based on interviews conducted with managers of institutions located in rural and urban areas of the Auvergne-Rhône-Alpes region (France). In order to situate the ESAT in their national context, a first section is devoted to recalling the genesis and functioning of this system, which was set up to promote the social and occupational integration of workers with disabilities, whose originality lies in the articulation of a medico-social logic with an economical logic. We then try to show how the ESAT have organized themselves to provide medico-social support for workers with disabilities despite the obligation of distancing. Then, analyzed through the prism of territorial anchoring and the concept of proximity associated with it, we will focus on the impact of confinement on the economic balance of these establishments to show that the health crisis has less affected the establishments in predominantly agricultural vocation established in rural areas than those, more oriented towards industrial subcontracting, located in urban areas.

The use of deep learning methods for virus identification from digital images is a timely research topic. Given an electron microscopy image, virus recognition utilizing deep learning approaches is critical at present, because virus identification by human experts is relatively slow and time-consuming. In this project, our objective is to develop deep learning methods for automatic virus identification from digital images, there are four viral species taken into consideration, namely, SARS, MERS, HIV, and COVID-19. In this work, we firstly examine virus morphological characteristics and propose a novel loss function which aims at virus identification from the given electron micrographs. We take into account of attention mechanism for virus locating and classification from digital images. In order to generate the most reliable estimate of bounding boxes and classification for a virus as visual object, we train and test five deep learning models: R-CNN, Fast R-CNN, Faster R-CNN, YOLO, and SSD, based on our dataset of virus electron microscopy. Additionally, we explicate the evaluation approaches. The conclusion reveals SSD and Faster R-CNN outperform in the virus identification.

Summary Telemedicine has become increasingly used by prison mental health services throughout the COVID-19 pandemic. In this editorial, we explore the benefits and risks of the remote provision of forensic mental healthcare, with consideration of the clinical, financial, ethical and legal consequences.

The novel Coronavirus infection disease is becoming more complex for the humans society by giving death and infected cases throughout the world. Due to this infection, many countries of the world suffers from great economic loss. The researchers around the world are very active to make a plan and policy for its early eradication. The government officials have taken full action for the eradication of this virus using different possible control strategies. It is the first priority of the researchers to develop safe vaccine against this deadly disease to minimize the infection. Different approaches have been made in this regards for its elimination. In this study, we formulate a mathematical epidemic model to analyze the dynamical behavior and transmission patterns of this new pandemic. We consider the environmental viral concentration in the model to better study the disease incidence in a community. Initially, the model is constructed with the derivative of integer-order. The classical epidemic model is then reconstructed with the fractional order operator in the form of Atangana-Baleanu derivative with the nonsingular and nonlocal kernel in order to analyze the dynamics of Coronavirus infection in a better way. A well-known estimation approach is used to estimate model parameters from the COVID-19 cases reported in Saudi Arabia from March 1 till August 20, 2020. After the procedure of parameters estimation, we explore some basic mathematical analysis of the fractional model. The stability results are provided for the disease free case using fractional stability concepts. Further, the uniqueness and existence results will be shown using the Picard-Lendelof approach. Moreover, an efficient numerical scheme has been proposed to obtain the solution of the model numerically. Finally, using the real fitted parameters, we depict many simulation results in order to demonstrate the importance of various model parameters and the memory index on disease dynamics and possible eradication.

Novel coronavirus pneumonia (COVID-19) is rampant in many countries and regions and there is no time to delay the exploration of the scheme for its prevention and control. The pathogenic characteristics of novel coronavirus and the effect of moxibustion for warming up yang and strengthening the antipathogenic qi were analyzed in this paper. From the perspective of modern medical mechanism, during the prevention and treatment of novel coronaviral infection, moxibustion may be able to prevent and treat COVID-19 by improving the body's immunity so as to conquer virus, by anti-inflammation to alleviate the inflammatory response of COVID-19 and by improving lung function to inhibit pulmonary fibrosis.

PurposeThis “impact pathways” paper argues that operations and supply chain management (OSCM) could help address the worsening drug shortage problem in high-income countries. This significant societal problem poses difficult challenges to stakeholders given the complex and dynamic nature of drug supply chains. OSCM scholars are well positioned to provide answers, introducing new research directions for OSCM in the process.Design/methodology/approachTo substantiate this, the authors carried out a review of stakeholder reports from six European countries and the academic literature.FindingsThere is little academic research and no fundamental agreement among stakeholders about causes of shortages. Stakeholders have suggested many government measures, but little evidence exists on their comparative cost-effectiveness.Originality/valueThe authors discuss three pathways of impactful research on drug shortages to which OSCM could contribute: (1) Developing an evidence-based system view of drug shortages; (2) Studying the comparative cost-effectiveness of key government interventions; (3) Bringing supply chain risk management into the government and economics perspectives and vice versa. Our study provides a baseline for future COVID-19-related research on this topic.

With the continuous progress of social science and technology, the development of the Internet of things is growing With the development of Internet of things, security problems emerge in endlessly During the period of COVID-19, the Internet of Things have been widely used to fight virus outbreak However, the most serious security problem of the Internet of things is network intrusion This paper proposes a balanced quadratic support vector machine information security analysis method for Internet of things Compared with the traditional support vector machine Internet of things security analysis method, this method has a higher accuracy, and can shorten the detection time, with efficient and powerful characteristics The method proposed in this paper has certain reference value to the Internet of things network intrusion problem It provides better security for the Internet of things during the protection period of covid-19 © 2020 - IOS Press and the authors All rights reserved

Vital sign monitoring is a common practice amongst medical professionals, and plays a key role in patient care and clinical diagnosis. Traditionally, dedicated equipment is employed to monitor these vital signs. For example, electrocardiograms (ECG) with 3-12 electrodes are attached to the target chest for heartbeat monitoring. In the last few years, wireless sensing becomes a hot research topic and wireless signal itself is utilized for sensing purposes without requiring the target to wear any sensors. The contact-free nature of wireless sensing makes it particularly appealing in current COVID-19 pandemic. Recently, promising progress has been achieved and the sensing granularity has been pushed to millimeter level, fine enough to monitor respiration which causes a chest displacement of 5 mm. While a great success with respiration monitoring, it is still very challenging to monitor heartbeat due to the extremely subtle chest displacement (0.1 - 0.5 mm) - smaller than 10% of that caused by respiration. What makes it worse is that the tiny heartbeat-caused chest displacement is buried inside the respiration-caused displacement. In this paper, we show the feasibility of employing the popular smart speakers (e.g., Amazon Echo) to monitor an individual's heartbeats in a contact-free manner. To extract the submillimeter heartbeat motion in the presence of other interference movements, a series of novel signal processing schemes are employed. We successfully prototype the first real-time heartbeat monitoring system using a commodity smart speaker. Experiment results show that the proposed system can monitor a target's heartbeat accurately, achieving a median heart rate estimation error of 0.75 beat per minute (bpm), and a median heartbeat interval estimation error of 13.28 ms (less than 1.8%), outperforming even some popular commodity products available on the market.

Ajeet Kumar, 1 Dan V Goia 2 1Ames Electronic Materials Division, South Plainfield, NJ 07080, USA; 2Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY, 13676, USACorrespondence: Dan V GoiaDepartment of Chemistry and Biomolecular Science, 123 Science Center, 8 Clarkson Ave, Potsdam, NY 13699, USATel +1 315 268 4411Email dgoia@clarkson.eduPurpose: The public fear associated with the novel coronavirus (SARS-CoV-2) pandemic has triggered recently a significant proliferation of supplements touted as potential cures against bacteria and viruses. Colloidal silver has particularly benefited from this rush given its empirically and scientifically documented anti-bacterial and anti-viral actions. The lack of standards in the unregulated supplements industry remains a major roadblock in evaluating the quality and consistency of marketed products or assessing the accuracy of the information provided by manufacturers. This study is the first scientifically rigorous attempt to evaluate commercial silver colloidal products offered for sale on the internet.Methods: Fourteen of the most popular colloidal silver products purchased from Amazon (www.amazon.com) were evaluated using state-of-the-art analytical techniques widely accepted as gold standards for investigating the properties (size, shape) and the dispersion of silver nanoparticles.Results: Commercial samples were analysed using UV-Vis, FE-SEM and AAS techniques. In general, the Ag concentration was very close to those claimed by the manufacturer. The colorless product shows no absorbance in the UV-Vis analysis. The FESEM and STEM images confirmed the conclusions of the UV-Vis analysis.Conclusion: The results of this evaluation show clearly that 70% of the commercial products evaluated contain only ionic silver. Despite the evidence showing that silver nanoparticles are not present, eight of these products are promoted by the manufacturers as ‘colloidal silver’. Considering the extensive scientific research showing major differences between silver ionic and silver nanoparticles in terms of mechanisms of action, efficacy and safety, it is clear that this misrepresentation impacts the consumers and must be addressed. This study serves as blueprint for a scientific protocol to be followed by manufacturers for characterizing their silver supplements.Keywords: colloidal silver, nanodispersion, bio-active, supplement, antimicrobial, UV-Vis analysis

The severe acute respiratory syndrome coronavirus 2 outbreak has had a significant impact on global health, the economy, and society as a whole. Various measures are being taken to respond to the pandemic, with digital media playing a pivotal role, especially in the use of visual data to disseminate information, mobile health to coordinate medical resources, social media to promote public health campaigns, and digital tools to assist population management and disease tracing. However, digital media also faces some challenges like misinformation, lack of guidance, and information leakage. We encourage the increased use of digital media with a focus on improving trust, building social solidarity, reducing chaos, educating the public on prevention measures, and reducing the medical burden in facility-based sites.